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论坛 计量经济学与统计论坛 五区 计量经济学与统计软件 winbugs及其他软件专版
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2017-04-23
h2o
This is the code and data repository for the "Practical Machine Learning with H2O" book, published by O'Reilly.
As well as direct from O'Reilly, it is also available in places like Amazon US and Amazon UK  ( Print ISBN: 978-1-4919-6460-6;   Ebook ISBN: 978-1-4919-6454-5 )
If you find any errors in the code found here, please file a bug report here. For mistakes or typos in the text of the book, use the book's errata page
If you have written your own code that gets a better result on one of the data sets in the book, and want to share, please submit a pull request by putting your contrib folder. Please make all contributions as public domain, or under the MIT or BSD open source license. Remember to include any additional data sets used (or links to them if they are already open and online somewhere stable).

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2017-4-23 04:04:05
Files by book chapter

###chapter 1
iris_deeplearning.py
iris_deeplearning.R
iris_deeplearning.reproducible.py
iris_deeplearning.reproducible.R


###chapter 2
drop_and_assign.py
drop_and_assign.R
load_from_dictionary.py
modify_columns.R


###chapter 3
analyze_football_bet_correlations.R
building_energy_correlations.py
load.building_energy.py
load.building_energy.R
load.building_energy.reproducible.py
load.building_energy.reproducible.R
load.football_2013_2014.py
load.football_2013_2014.R
load.football2.py
load.football2.R
load.football.py
load.football.R
load.mnist.py
load.mnist.R
load.mnist.reproducible.py
load.mnist.reproducible.R
mnist_manipulation.py


###chapter 4
early_stopping_example.py
early_stopping_example.reproducible.py
misbalanced_classes.example.R
misbalanced_classes.reproducible.R
using_checkpoints.py
using_checkpoints.R


###chapter 5
compare_models.R
random_forest.building_energy.default.py
random_forest.building_energy.default.R
random_forest.building_energy.default.reproducible.py
random_forest.building_energy.grid1.py
random_forest.building_energy.grid1.R
random_forest.building_energy.grid2.R
random_forest.building_energy.lapply_seed.R
random_forest.football.default.py
random_forest.football.default.reproducible.py
random_forest.mnist.default.py
random_forest.mnist.default.R
random_forest.mnist.default.reproducible.py


###chapter 6
gbm.building_energy.default.R
gbm.building_energy.default.reproducible.py
gbm.building_energy.default.reproducible.R


###chapter 9
autoencoder.tfidf.py
autoencoder.tfidf.R
glrm.tfidf.R
kmeans.tfidf.py
kmeans.tfidf.R
prcomp.tfidf.R


###chapter 11
epilogue_comparison.building_energy.R
epilogue_comparison.football.R
epilogue_comparison.mnist.R
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2017-4-23 04:05:46
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2017-4-23 04:07:13
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2017-4-23 04:09:21
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2017-4-23 04:10:18
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